Abstract Measuring and targeting energy performances of manufacturing plants and their subsystems is the first, critical step to understand their energy behavior, to identify energy management opportunities and to evaluate energy savings. In addition, this activity has become always more important in the last decades, as Energy Management Systems and energy management practices based on continuous improvement and people engagement have been largely adopted, requiring the introduction of new energy consumption control systems capable to identify the standard operative energy behavior and performance of systems and machines and their energy baseline, to point out contingent deviations of energy performances from the baseline and to identify possible causes and clearly attribute responsibilities of such deviations. In this context, several attempts have been presented in literature trying to identify methods to create Energy Performance Indicators so as to satisfy these requirements, but most of them are focused either on a physical or on economical definition of the problem (and therefore either on a process/appliance level or on an aggregated level), neglecting the necessity to develop an integrated system to combine those two approaches to the problem and deliver appropriate information to each hierarchical level and function of the company. In addition, even when these indicators are identified, a proper system to monitor and control their evolution over time is neglected. In this paper, a novel methodology to manage Energy Performance by developing, analyzing and maintaining Energy Performance Indicators in manufacturing plants is presented, which has been created to fill this gap and taking into account ISO 50001:2011 and ISO 50006:2014 requirements, in order to be as general and widely applicable as possible. The proposed methodology allows an immediate identification of manufacturing plant's energy performance deviations through Energy Performance Indicators monitoring over time and an easy association of causes and responsibilities to such deviations, in order to allow companies to rapidly react defining action plans and resetting targets if necessary; it has also been validated through an industrial case study, which will eventually be presented.